180 lines
5.4 KiB
JavaScript
180 lines
5.4 KiB
JavaScript
|
function option1 (curSelected) {
|
|||
|
|
var option = {
|
|||
|
|
color: ['#87cefa','#ff7f50','#da70d6','#32cd32','#6495ed',
|
|||
|
|
'#ff69b4','#ba55d3','#cd5c5c','#ffa500','#40e0d0',
|
|||
|
|
'#1e90ff','#ff6347','#7b68ee','#00fa9a','#ffd700',
|
|||
|
|
'#6699FF','#ff6666','#3cb371','#b8860b','#30e0e0'],
|
|||
|
|
title : {
|
|||
|
|
subtext: '数据来自国家统计局'
|
|||
|
|
},
|
|||
|
|
tooltip : {
|
|||
|
|
trigger: 'axis'
|
|||
|
|
},
|
|||
|
|
legend: {
|
|||
|
|
data : ['GDP','金融','房地产','第一产业','第二产业','第三产业'],
|
|||
|
|
selected : curSelected
|
|||
|
|
},
|
|||
|
|
toolbox: {
|
|||
|
|
show : true,
|
|||
|
|
feature : {
|
|||
|
|
mark : {show: true},
|
|||
|
|
dataView : {show: true, readOnly: false},
|
|||
|
|
magicType : {show: true, type: ['line', 'bar', 'stack', 'tiled']},
|
|||
|
|
restore : {show: true},
|
|||
|
|
saveAsImage : {show: true}
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
calculable : true,
|
|||
|
|
grid : {
|
|||
|
|
y : 80,
|
|||
|
|
y2 : 100,
|
|||
|
|
},
|
|||
|
|
xAxis : [
|
|||
|
|
{
|
|||
|
|
type : 'category',
|
|||
|
|
axisLabel: {
|
|||
|
|
interval: 0
|
|||
|
|
},
|
|||
|
|
data : [
|
|||
|
|
'北京','\n天津','河北','\n山西','内蒙古','\n辽宁',
|
|||
|
|
'吉林','\n黑龙江','上海','\n江苏','浙江','\n安徽',
|
|||
|
|
'福建','\n江西','山东','\n河南','湖北','\n湖南',
|
|||
|
|
'广东','\n广西','海南','\n重庆','四川','\n贵州',
|
|||
|
|
'云南','\n西藏','陕西','\n甘肃','青海','\n宁夏','新疆'
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
yAxis : [
|
|||
|
|
{
|
|||
|
|
type : 'value',
|
|||
|
|
name : 'GDP（亿元）',
|
|||
|
|
max: 53500,
|
|||
|
|
splitArea : {show : true}
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
type : 'value',
|
|||
|
|
name : '其他（亿元）',
|
|||
|
|
splitArea : {show : true}
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
series : [
|
|||
|
|
{
|
|||
|
|
name:'GDP',
|
|||
|
|
_name: 'GDP',
|
|||
|
|
type:'bar',
|
|||
|
|
markLine: {
|
|||
|
|
symbol : ['arrow','none'],symbolSize : [4, 2],itemStyle : {normal: {
|
|||
|
|
lineStyle: {color:'orange'},
|
|||
|
|
borderColor:'orange',
|
|||
|
|
label:{position:'left',formatter:function(params){return Math.round(params.value)},
|
|||
|
|
textStyle:{color:"orange"}
|
|||
|
|
}}},
|
|||
|
|
data : [
|
|||
|
|
{type : 'average', name : '平均值'}
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'金融',
|
|||
|
|
_name: 'Financial',
|
|||
|
|
yAxisIndex: 1,
|
|||
|
|
type:'bar'
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'房地产',
|
|||
|
|
_name: 'Estate',
|
|||
|
|
yAxisIndex: 1,
|
|||
|
|
type:'bar'
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第一产业',
|
|||
|
|
_name: 'PI',
|
|||
|
|
yAxisIndex: 1,
|
|||
|
|
type:'bar'
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第二产业',
|
|||
|
|
_name: 'SI',
|
|||
|
|
yAxisIndex: 1,
|
|||
|
|
type:'bar'
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第三产业',
|
|||
|
|
_name: 'TI',
|
|||
|
|
yAxisIndex: 1,
|
|||
|
|
type:'bar'
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
};
|
|||
|
|
|
|||
|
|
var timelineOption = {
|
|||
|
|
timeline : {
|
|||
|
|
data : (function(){
|
|||
|
|
var a = [];
|
|||
|
|
for (var i = 2002; i <= 2011; i++) {
|
|||
|
|
a.push(i + '-01-01');
|
|||
|
|
}
|
|||
|
|
return a;
|
|||
|
|
})(),
|
|||
|
|
label : {
|
|||
|
|
formatter : function(s) {
|
|||
|
|
return s.slice(0, 4);
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
playInterval : 1000
|
|||
|
|
},
|
|||
|
|
options : []
|
|||
|
|
};
|
|||
|
|
|
|||
|
|
var curYear = 2002;
|
|||
|
|
option.title.text = curYear + '全国宏观经济指标'
|
|||
|
|
for (var i = 0, l = option.series.length; i < l; i++) {
|
|||
|
|
option.series[i].data = dataMap['data' + option.series[i]._name][curYear]
|
|||
|
|
}
|
|||
|
|
timelineOption.options.push(option);
|
|||
|
|
|
|||
|
|
for (curYear = 2003; curYear <= 2011; curYear++) {
|
|||
|
|
var newSeries = [
|
|||
|
|
{
|
|||
|
|
name:'GDP',
|
|||
|
|
_name: 'GDP'
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'金融',
|
|||
|
|
_name: 'Financial',
|
|||
|
|
yAxisIndex: 1
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'房地产',
|
|||
|
|
_name: 'Estate',
|
|||
|
|
yAxisIndex: 1
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第一产业',
|
|||
|
|
_name: 'PI',
|
|||
|
|
yAxisIndex: 1
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第二产业',
|
|||
|
|
_name: 'SI',
|
|||
|
|
yAxisIndex: 1
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
name:'第三产业',
|
|||
|
|
_name: 'TI',
|
|||
|
|
yAxisIndex: 1
|
|||
|
|
}
|
|||
|
|
];
|
|||
|
|
|
|||
|
|
for (var i = 0, l = newSeries.length; i < l; i++) {
|
|||
|
|
newSeries[i].data = dataMap['data' + newSeries[i]._name][curYear]
|
|||
|
|
}
|
|||
|
|
timelineOption.options.push({
|
|||
|
|
title : {
|
|||
|
|
text : curYear + '全国宏观经济指标'
|
|||
|
|
},
|
|||
|
|
series : newSeries
|
|||
|
|
})
|
|||
|
|
}
|
|||
|
|
return timelineOption;
|
|||
|
|
}
|